3D MPRAGE improves classification of cortical lesions in multiple sclerosis.

BACKGROUND: Gray matter lesions are known to be common in multiple sclerosis (MS) and are suspected to play an important role in disease progression and clinical disability. A combination of magnetic resonance imaging (MRI) techniques, double-inversion recovery (DIR), and phase-sensitive inversion recovery (PSIR), has been used for detection and classification of cortical lesions. This study shows that high-resolution three-dimensional (3D) magnetization-prepared rapid acquisition with gradient echo (MPRAGE) improves the classification of cortical lesions by allowing more accurate anatomic localization of lesion morphology. METHODS: 11 patients with MS with previously identified cortical lesions were scanned using DIR, PSIR, and 3D MPRAGE. Lesions were identified on DIR and PSIR and classified as purely intracortical or mixed. MPRAGE images were then examined, and lesions were re-classified based on the new information. RESULTS: The high signal-to-noise ratio, fine anatomic detail, and clear gray-white matter tissue contrast seen in the MPRAGE images provided superior delineation of lesion borders and surrounding gray-white matter junction, improving classification accuracy. 119 lesions were identified as either intracortical or mixed on DIR/PSIR. In 89 cases, MPRAGE confirmed the classification by DIR/PSIR. In 30 cases, MPRAGE overturned the original classification. CONCLUSION: Improved classification of cortical lesions was realized by inclusion of high-spatial resolution 3D MPRAGE. This sequence provides unique detail on lesion morphology that is necessary for accurate classification.

EXPRESSION AND IMMUNOLOGICAL CHARACTERIZATION OF HERV-K TRANSMEMBRANE ENVELOPE PROTEIN IN HUMAN BREAST CANCER

The human endogenous retrovirus K (HERV-K) env gene encodes envelope protein comprising surface (SU) and transmembrane (TM) domains. Having shown the exclusive expression of SU in human breast cancer and the stimulation of SU-specific immune responses in patients with breast cancer, our research here confirmed and extended the data by investigating the expression of HERV-K TM envelope domain and the induction of specific immune responses against TM in breast cancer patients. We found HERV-K TM mRNA and protein expression only in human breast cancer cells but not in normal controls. The specific immune responses against TM domain were induced in mice determined by enzyme-linked immunosorbent assay (ELISA) and IFN-γ enzyme-linked immunosorbent spot (ELISPOT) assay. Furthermore, ELISA detected higher titers of anti-HERV-K TM Env IgG antibodies in sera of breast cancer patients. In addition, the magnitude of the anti-HERV TM B cell response was correlated with the disease stage. Peripheral blood mononuclear cells (PBMCs) before and after in vitro stimulation (IVS) with HERV-K TM from patients with breast cancer as well as healthy controls were tested for T cell responses against HERV-K TM domain by ELISPOT assay. Breast cancer patients (n=21) had stronger HERV-K TM-specific cellular responses than healthy controls (n=12) (P < 0.05). These findings suggest, for the first time, that HERV-K TM expression was enhanced in human breast cancer cells and was able to induce specific B cell and T cell immune responses in breast cancer patients. This study provides support for HERV-K TM as a promising source of antigen for anti-tumor immunotherapy, prevention, diagnosis, and prognosis.

Selective elevation of c-{\it myc} RNA transcripts during clonal evolution of N-methyl-N-nitrosourea induced thymic lymphomas in AKR/J mice

Untreated AKR mice develop spontaneous thymic lymphomas by 6-12 months of age. Lymphoma development is accelerated when young mice are injected with the carcinogen N-methyl-N-nitrosourea (MNU). Selected molecular and cellular events were compared during the latent period preceding "spontaneous" (retrovirally-induced) and MNU-induced thymic lymphoma development in AKR mice. These studies were undertaken to test the hypothesis that thymic lymphomas induced in the same inbred mouse strain by endogenous retroviruses and by a chemical carcinogen develop by different mechanisms.^ Immunofluorescence analysis of differentiation antigens showed that most MNU-induced lymphomas express an immature CD4-8+ profile. In contrast, spontaneous lymphomas represent each of the major lymphocyte subsets. These data suggest involvement of different target populations in MNU-induced and spontaneous lymphomas. Analyses at intervals after MNU treatment revealed selective expansion of the CD4-8+ J11d+ thymocyte subset at 8-10 weeks post-MNU in 68% of the animals examined, suggesting that these cells are targets for MNU-induced lymphomagenesis. Untreated age-matched animals showed no selective expansion of thymocyte subsets.^ Previous data have shown that both spontaneous and MNU-induced lymphomas are monoclonal or oligoclonal. Distinct rearrangement patterns of the J$\sb2$ region of the T-cell receptor $\beta$-chain showed emergence of clonal thymocyte populations beginning at 6-7 weeks after MNU treatment. However, lymphocytes from untreated animals showed no evidence of clonal expansion at the time intervals investigated.^ Activation of c-myc frequently occurs during development of B- and T- cell lymphomas. Both spontaneous and MNU-induced lymphomas showed increased c-myc transcript levels. Increased c-myc transcription was first detected at 6 weeks post-MNU, and persisted throughout the latent period. However, untreated animals showed no increases in c-myc transcripts at the time intervals examined. Another nuclear oncogene, c-fos, did not display a similar change in RNA transcription during the latent period.^ These results supports the hypothesis that MNU-induced and spontaneous tumors develop by multi-step pathways which are distinct with respect to the target cell population affected. Clonal emergence and c-myc deregulation are important steps in the development of both MNU-induced and spontaneous tumors, but the onset of these events is later in spontaneous tumor development. ^

Combining Monte Carlo methods with coherent wave optics for the simulation of phase-sensitive X-ray imaging

Phase-sensitive X-ray imaging shows a high sensitivity towards electron density variations, making it well suited for imaging of soft tissue matter. However, there are still open questions about the details of the image formation process. Here, a framework for numerical simulations of phase-sensitive X-ray imaging is presented, which takes both particle- and wave-like properties of X-rays into consideration. A split approach is presented where we combine a Monte Carlo method (MC) based sample part with a wave optics simulation based propagation part, leading to a framework that takes both particle- and wave-like properties into account. The framework can be adapted to different phase-sensitive imaging methods and has been validated through comparisons with experiments for grating interferometry and propagation-based imaging. The validation of the framework shows that the combination of wave optics and MC has been successfully implemented and yields good agreement between measurements and simulations. This demonstrates that the physical processes relevant for developing a deeper understanding of scattering in the context of phase-sensitive imaging are modelled in a sufficiently accurate manner. The framework can be used for the simulation of phase-sensitive X-ray imaging, for instance for the simulation of grating interferometry or propagation-based imaging.

Classification of platelet concentrates (Platelet-Rich Plasma-PRP, Platelet-Rich Fibrin-PRF) for topical and infiltrative use in orthopedic and sports medicine: current consensus, clinical implications and perspectives.

Platelet concentrates for topical and infiltrative use - commonly termed Platetet-Rich Plasma (PRP) or Platelet-Rich Fibrin (PRF) - are used or tested as surgical adjuvants or regenerative medicine preparations in most medical fields, particularly in sports medicine and orthopaedic surgery. Even if these products offer interesting therapeutic perspectives, their clinical relevance is largely debated, as the literature on the topic is often confused and contradictory. The long history of these products was always associated with confusions, mostly related to the lack of consensual terminology, characterization and classification of the many products that were tested in the last 40 years. The current consensus is based on a simple classification system dividing the many products in 4 main families, based on their fibrin architecture and cell content: Pure Platelet-Rich Plasma (P-PRP), such as the PRGF-Endoret technique; Leukocyte- and Platelet-Rich Plasma (LPRP), such as Biomet GPS system; Pure Platelet-Rich Fibrin (P-PRF), such as Fibrinet; Leukocyte- and Platelet-Rich Fibrin (L-PRF), such as Intra-Spin L-PRF. The 4 main families of products present different biological signatures and mechanisms, and obvious differences for clinical applications. This classification serves as a basis for further investigations of the effects of these products. Perspectives of evolutions of this classification and terminology are also discussed, particularly concerning the impact of the cell content, preservation and activation on these products in sports medicine and orthopaedics.

Żydzi Lwowscy na przełomie XVIgo i XVIIgo wieku : praca odznaczona pierwszą nagrodą na konkursie im. H. Wawelberga przez wydział filozoficzny C. K. Uniwersytetu Lwowskiego

Majer Bałaban

Classification of interstitial lung disease patterns using local DCT features and random forest.

Over the last decade, a plethora of computer-aided diagnosis (CAD) systems have been proposed aiming to improve the accuracy of the physicians in the diagnosis of interstitial lung diseases (ILD). In this study, we propose a scheme for the classification of HRCT image patches with ILD abnormalities as a basic component towards the quantification of the various ILD patterns in the lung. The feature extraction method relies on local spectral analysis using a DCT-based filter bank. After convolving the image with the filter bank, q-quantiles are computed for describing the distribution of local frequencies that characterize image texture. Then, the gray-level histogram values of the original image are added forming the final feature vector. The classification of the already described patches is done by a random forest (RF) classifier. The experimental results prove the superior performance and efficiency of the proposed approach compared against the state-of-the-art.

Biographical sketch of Dr. K. Kohler

by Max J. Kohler

Fully automatic segmentation of AP pelvis X-rays via random forest regression with efficient feature selection and hierarchical sparse shape composition

In clinical practice, traditional X-ray radiography is widely used, and knowledge of landmarks and contours in anteroposterior (AP) pelvis X-rays is invaluable for computer aided diagnosis, hip surgery planning and image-guided interventions. This paper presents a fully automatic approach for landmark detection and shape segmentation of both pelvis and femur in conventional AP X-ray images. Our approach is based on the framework of landmark detection via Random Forest (RF) regression and shape regularization via hierarchical sparse shape composition. We propose a visual feature FL-HoG (Flexible- Level Histogram of Oriented Gradients) and a feature selection algorithm based on trace radio optimization to improve the robustness and the efficacy of RF-based landmark detection. The landmark detection result is then used in a hierarchical sparse shape composition framework for shape regularization. Finally, the extracted shape contour is fine-tuned by a post-processing step based on low level image features. The experimental results demonstrate that our feature selection algorithm reduces the feature dimension in a factor of 40 and improves both training and test efficiency. Further experiments conducted on 436 clinical AP pelvis X-rays show that our approach achieves an average point-to-curve error around 1.2 mm for femur and 1.9 mm for pelvis.

Quaternary uplift rates of the Central Anatolian Plateau, Turkey: insights from cosmogenic isochron-burial nuclide dating of the Kızılırmak River terraces

The Central Anatolian Plateau (CAP) in Turkey is a relatively small plateau (300 × 400 km) with moderate average elevations of ∼1 km situated between the Pontide and Tauride orogenic mountain belts. Kızılırmak, which is the longest river (1355 km) within the borders of Turkey, flows within the CAP and slowly incises into lacustrine and volcaniclastic units before finally reaching the Black Sea. We dated the Cappadocia section of the Kızılırmak terraces in the CAP by using cosmogenic burial and isochron-burial dating methods with 10Be and 26Al as their absolute dating can provide insight into long-term incision rates, uplift and climatic changes. Terraces at 13, 20, 75 and 100 m above the current river indicate an average incision rate of 0.051 ± 0.01 mm/yr (51 ± 1 m/Ma) since ∼1.9 Ma. Using the base of a basalt fill above the modern course of the Kızılırmak, we also calculated 0.05–0.06 mm/yr mean incision and hence rock uplift rate for the last 2 Ma. Although this rate might be underestimated due to normal faulting along the valley sides, it perfectly matches our results obtained from the Kızılırmak terraces. Although up to 5–10 times slower, the Quaternary uplift of the CAP is closely related to the uplift of the northern and southern plateau margins respectively.